Autocorrection in MR imaging: adaptive motion correction without navigator echoes

Towards retrospective motion correction and reconstruction for clinical 3D brain MRI protocols with a reference contrast

OBJECT

In a typical MR session, several contrasts are acquired. Due to the sequential nature of the data acquisition process, the patient may experience some discomfort at some point during the session, and start moving. Hence, it is quite common to have MR sessions where some contrasts are well-resolved, while other contrasts exhibit motion artifacts. Instead of repeating the scans that are corrupted by motion, we introduce a reference-guided retrospective motion correction scheme that takes advantage of the motion-free scans, based on a generalized rigid registration routine.

MATERIALS AND METHODS

We focus on various existing clinical 3D brain protocols at 1.5 Tesla MRI based on Cartesian sampling. Controlled experiments with three healthy volunteers and three levels of motion are performed.

RESULTS

Radiological inspection confirms that the proposed method consistently ameliorates the corrupted scans. Furthermore, for the set of specific motion tests performed in this study, the quality indexes based on PSNR and SSIM shows only a modest decrease in correction quality as a function of motion complexity.

DISCUSSION

While the results on controlled experiments are positive, future applications to patient data will ultimately clarify whether the proposed correction scheme satisfies the radiological requirements.

A k-space-based method to measure and correct for temporal B0 field variations in MR temperature imaging

PURPOSE

Present a method to use change in phase in repeated Cartesian k-space measurements to monitor the change in magnetic field for dynamic MR temperature imaging.

METHODS

The method is applied to focused ultrasound heating experiments in a gelatin phantom and an ex vivo salt pork sample, without and with simulated respiratory motion.

RESULTS

In each experiment, phase variations due to B0 field drift and respiration were readily apparent in the measured phase difference. With correction, the SD of the temperature over time was reduced from 0.18°C to 0.14°C (no breathing) and from 0.81°C to 0.22°C (with breathing) for the gelatin phantom, and from 0.68°C to 0.13°C (no breathing) and from 1.06°C to 0.17°C (with breathing) for the pork sample. The accuracy in nonheated regions, assessed as the RMS error deviation from 0°C, improved from 1.70°C to 1.11°C (no breathing) and from 4.73°C to 1.47°C (with breathing) for the gelatin phantom, and from 5.95°C to 0.88°C (no breathing) and from 13.40°C to 1.73°C (with breathing) for the pork sample. The correction did not affect the temperature measurement accuracy in the heated regions.

CONCLUSION

This work demonstrates that phase changes resulting from variations in B0 due to drift and respiration, commonly seen in MR thermometry applications, can be measured directly from 3D Cartesian acquisition methods. The correction of temporal field variations using the presented technique improved temperature accuracy, reduced variability in nonheated regions, and did not reduce accuracy in heated regions.

Correction of out-of-FOV motion artifacts using convolutional neural network

PURPOSE

Subject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-FOV motion happens. Currently available algorithms are not able to correct for image artifacts introduced by out-of-FOV motion. The purpose of this study is to demonstrate the feasibility of incorporating convolutional neural network (CNN) derived prior image into solving the out-of-FOV motion problem.

METHODS AND MATERIALS

A modified U-net network was proposed to correct out-of-FOV motion artifacts by incorporating motion parameters into the loss function. A motion model based data fidelity term was applied in combination with the CNN prediction to further improve the motion correction performance. We trained the CNN on 1113 MPRAGE images with simulated oscillating and sudden motion trajectories, and compared our algorithm to a gradient-based autofocusing (AF) algorithm in both 2D and 3D images. Additional experiment was performed to demonstrate the feasibility of transferring the networks to different dataset. We also evaluated the robustness of this algorithm by adding Gaussian noise to the motion parameters. The motion correction performance was evaluated using mean square error (NMSE), peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).

RESULTS

The proposed algorithm outperformed AF-based algorithm for both 2D (NMSE: 0.0066 ± 0.0009 vs 0.0141 ± 0.008, P < .01; PSNR: 29.60 ± 0.74 vs 21.71 ± 0.27, P < .01; SSIM: 0.89 ± 0.014 vs 0.73 ± 0.004, P < .01) and 3D imaging (NMSE: 0.0067 ± 0.0008 vs 0.070 ± 0.021, P < .01; PSNR: 32.40 ± 1.63 vs 22.32 ± 2.378, P < .01; SSIM: 0.89 ± 0.01 vs 0.62 ± 0.03, P < .01). Robust reconstruction was achieved with 20% data missed due to the out-of-FOV motion.

CONCLUSION

In conclusion, the proposed CNN-based motion correction algorithm can significantly reduce out-of-FOV motion artifacts and achieve better image quality compared to AF-based algorithm.

Retrospective Brain Motion Correction in Glutamate Chemical Exchange Saturation Transfer (GluCEST) MRI

PURPOSE

To evaluate the feasibility of motion correction in glutamate chemical exchange saturation transfer (GluCEST) imaging, using a rat model of epileptic seizure.

PROCEDURES

Epileptic seizure was induced in six male Wistar rats by intraperitoneal injection of kainic acid (KA). CEST data were obtained using a 7.0 T Bruker MRI scanner before and 3 h after KA injection. Retrospective motion correction was performed in CEST images using a gradient-based motion correction (GradMC) algorithm. GluCEST signals in the hippocampal regions were quantitatively evaluated with and without motion correction.

RESULTS

Calculated GluCEST signals differed significantly between the pre-KA injection group, regardless of motion-correction implementation, and the post-KA injection group with motion correction (3.662 ± 1.393 % / 3.726 ± 1.982 % for pre-KA injection group with/without motion correction vs. 6.996 ± 1.684 % for post-KA injection group with motion correction; all P < 0.05).

CONCLUSIONS

Our results clearly show that GradMC can be used in CEST imaging for efficient correction of seizure-like motion. The GradMC can be further implemented in various CEST imaging techniques to increase the accuracy of analysis.

Nonrigid Motion Correction With 3D Image-Based Navigators for Coronary MR Angiography

PURPOSE

To develop a retrospective nonrigid motion-correction method based on 3D image-based navigators (iNAVs) for free-breathing whole-heart coronary magnetic resonance angiography (MRA).

METHODS

The proposed method detects global rigid-body motion and localized nonrigid motion from 3D iNAVs and compensates them with an autofocusing algorithm. To model the global motion, 3D rotation and translation are estimated from the 3D iNAVs. Two sets of localized nonrigid motions are obtained from deformation fields between 3D iNAVs and reconstructed binned images, respectively. A bank of motion-corrected images is generated and the final image is assembled pixel-by-pixel by selecting the best focused pixel from this bank. In vivo studies with six healthy volunteers were conducted to compare the performance of the proposed method with 3D translational motion correction and no correction.

RESULTS

In vivo studies showed that compared to no correction, 3D translational motion correction and the proposed method increased the vessel sharpness by 13% ± 13% and 19% ± 16%, respectively. Out of 90 vessel segments, 75 segments showed improvement with the proposed method compared to 3D translational correction.

CONCLUSION

We have developed a nonrigid motion-correction method based on 3D iNAVs and an autofocusing algorithm that improves the vessel sharpness of free-breathing whole-heart coronary MRA. Magn Reson Med 77:1884-1893, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

A radial sampling strategy for uniform k-space coverage with retrospective respiratory gating in 3D ultrashort-echo-time lung imaging

The purpose of this work was to develop a 3D radial-sampling strategy which maintains uniform k-space sample density after retrospective respiratory gating, and demonstrate its feasibility in free-breathing ultrashort-echo-time lung MRI. A multi-shot, interleaved 3D radial sampling function was designed by segmenting a single-shot trajectory of projection views such that each interleaf samples k-space in an incoherent fashion. An optimal segmentation factor for the interleaved acquisition was derived based on an approximate model of respiratory patterns such that radial interleaves are evenly accepted during the retrospective gating. The optimality of the proposed sampling scheme was tested by numerical simulations and phantom experiments using human respiratory waveforms. Retrospectively, respiratory-gated, free-breathing lung MRI with the proposed sampling strategy was performed in healthy subjects. The simulation yielded the most uniform k-space sample density with the optimal segmentation factor, as evidenced by the smallest standard deviation of the number of neighboring samples as well as minimal side-lobe energy in the point spread function. The optimality of the proposed scheme was also confirmed by minimal image artifacts in phantom images. Human lung images showed that the proposed sampling scheme significantly reduced streak and ring artifacts compared with the conventional retrospective respiratory gating while suppressing motion-related blurring compared with full sampling without respiratory gating. In conclusion, the proposed 3D radial-sampling scheme can effectively suppress the image artifacts due to non-uniform k-space sample density in retrospectively respiratory-gated lung MRI by uniformly distributing gated radial views across the k-space.

Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI

While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among "good quality" structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects' tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion-even at levels which do not manifest in visible motion artifact-can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans. Hum Brain Mapp 37:2385-2397, 2016. © 2016 Wiley Periodicals, Inc.

Motion correction in MRI of the brain

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed.

Accuracy and Precision of Head Motion Information in Multi-Channel Free Induction Decay Navigators for Magnetic Resonance Imaging

Free induction decay (FID) navigators were found to qualitatively detect rigid-body head movements, yet it is unknown to what extent they can provide quantitative motion estimates. Here, we acquired FID navigators at different sampling rates and simultaneously measured head movements using a highly accurate optical motion tracking system. This strategy allowed us to estimate the accuracy and precision of FID navigators for quantification of rigid-body head movements. Five subjects were scanned with a 32-channel head coil array on a clinical 3T MR scanner during several resting and guided head movement periods. For each subject we trained a linear regression model based on FID navigator and optical motion tracking signals. FID-based motion model accuracy and precision was evaluated using cross-validation. FID-based prediction of rigid-body head motion was found to be with a mean translational and rotational error of 0.14±0.21 mm and 0.08±0.13°, respectively. Robust model training with sub-millimeter and sub-degree accuracy could be achieved using 100 data points with motion magnitudes of ±2 mm and ±1° for translation and rotation. The obtained linear models appeared to be subject-specific as inter-subject application of a "universal" FID-based motion model resulted in poor prediction accuracy. The results show that substantial rigid-body motion information is encoded in FID navigator signal time courses. Although, the applied method currently requires the simultaneous acquisition of FID signals and optical tracking data, the findings suggest that multi-channel FID navigators have a potential to complement existing tracking technologies for accurate rigid-body motion detection and correction in MRI.

Registration-based autofocusing technique for automatic correction of motion artifacts in time-series studies of high-resolution bone MRI

PURPOSE

To develop a registration-based autofocusing (RAF) motion correction technique for high-resolution trabecular bone (TB) imaging and to evaluate its performance on in vivo MR data.

MATERIALS AND METHODS

The technique combines serial registration with a previously developed motion correction technique - autofocusing - for automatic correction of subject movement degradation of MR images acquired in longitudinal studies. The method was tested on in vivo images of the distal radius to measure improvements in serial reproducibility of parameters in 12 women (ages 50-75 years), and to compare with the navigator echo-based correction and autofocusing. Furthermore, the technique's ability to optimize the sensitivity to detect simulated bone loss was ascertained.

RESULTS

The new technique yielded superior reproducibility of image-derived structural and mechanical parameters. Average coefficient of variation across all parameters improved by 12.5%, 27.0%, 33.5%, and 37.0%, respectively, following correction by navigator echoes, autofocusing, and the RAF technique (without and with correction for rotational motion); average intra-class correlation coefficient increased by 1.2%, 2.2%, 2.8%, and 3.2%, respectively. Furthermore, simulated bone loss (5%) was well recovered independent of the choice of reference image (4.71% or 4.86% with respect to using either the original or the image subjected to bone loss) in the time series.

CONCLUSION

The data suggest that our technique simultaneously corrects for intra-scan motion corruption while improving inter-scan registration. Furthermore, the technique is not biased by small changes in bone architecture between time-points.

Nonrigid autofocus motion correction for coronary MR angiography with a 3D cones trajectory

PURPOSE

To implement a nonrigid autofocus motion correction technique to improve respiratory motion correction of free-breathing whole-heart coronary magnetic resonance angiography acquisitions using an image-navigated 3D cones sequence.

METHODS

2D image navigators acquired every heartbeat are used to measure superior-inferior, anterior-posterior, and right-left translation of the heart during a free-breathing coronary magnetic resonance angiography scan using a 3D cones readout trajectory. Various tidal respiratory motion patterns are modeled by independently scaling the three measured displacement trajectories. These scaled motion trajectories are used for 3D translational compensation of the acquired data, and a bank of motion-compensated images is reconstructed. From this bank, a gradient entropy focusing metric is used to generate a nonrigid motion-corrected image on a pixel-by-pixel basis. The performance of the autofocus motion correction technique is compared with rigid-body translational correction and no correction in phantom, volunteer, and patient studies.

RESULTS

Nonrigid autofocus motion correction yields improved image quality compared to rigid-body-corrected images and uncorrected images. Quantitative vessel sharpness measurements indicate superiority of the proposed technique in 14 out of 15 coronary segments from three patient and two volunteer studies.

CONCLUSION

The proposed technique corrects nonrigid motion artifacts in free-breathing 3D cones acquisitions, improving image quality compared to rigid-body motion correction.

Blind retrospective motion correction of MR images

PURPOSE

Subject motion can severely degrade MR images. A retrospective motion correction algorithm, Gradient-based motion correction, which significantly reduces ghosting and blurring artifacts due to subject motion was proposed. The technique uses the raw data of standard imaging sequences; no sequence modifications or additional equipment such as tracking devices are required. Rigid motion is assumed.

METHODS

The approach iteratively searches for the motion trajectory yielding the sharpest image as measured by the entropy of spatial gradients. The vast space of motion parameters is efficiently explored by gradient-based optimization with a convergence guarantee.

RESULTS

The method has been evaluated on both synthetic and real data in two and three dimensions using standard imaging techniques. MR images are consistently improved over different kinds of motion trajectories. Using a graphics processing unit implementation, computation times are in the order of a few minutes for a full three-dimensional volume.

CONCLUSION

The presented technique can be an alternative or a complement to prospective motion correction methods and is able to improve images with strong motion artifacts from standard imaging sequences without requiring additional data.

An embedded optical tracking system for motion-corrected magnetic resonance imaging at 7T

OBJECT

Prospective motion correction using data from optical tracking systems has been previously shown to reduce motion artifacts in MR imaging of the head. We evaluate a novel optical embedded tracking system.

MATERIALS AND METHODS

The home-built optical embedded tracking system performs image processing within a 7 T scanner bore, enabling high speed tracking. Corrected and uncorrected in vivo MR volumes are acquired interleaved using a modified 3D FLASH sequence, and their image quality is assessed and compared.

RESULTS

The latency between motion and correction of the slice position was measured to be (19 ± 5) ms, and the tracking noise has a standard deviation no greater than 10 μm/0.005° during conventional MR scanning. Prospective motion correction improved the edge strength by 16 % on average, even though the volunteers were asked to remain motionless during the acquisitions.

CONCLUSION

Using a novel method for validating the effectiveness of in vivo prospective motion correction, we have demonstrated that prospective motion correction using motion data from the embedded tracking system considerably improved image quality.

Nonrigid motion correction in 3D using autofocusing with localized linear translations

MR scans are sensitive to motion effects due to the scan duration. To properly suppress artifacts from nonrigid body motion, complex models with elements such as translation, rotation, shear, and scaling have been incorporated into the reconstruction pipeline. However, these techniques are computationally intensive and difficult to implement for online reconstruction. On a sufficiently small spatial scale, the different types of motion can be well approximated as simple linear translations. This formulation allows for a practical autofocusing algorithm that locally minimizes a given motion metric--more specifically, the proposed localized gradient-entropy metric. To reduce the vast search space for an optimal solution, possible motion paths are limited to the motion measured from multichannel navigator data. The novel navigation strategy is based on the so-called "Butterfly" navigators, which are modifications of the spin-warp sequence that provides intrinsic translational motion information with negligible overhead. With a 32-channel abdominal coil, sufficient number of motion measurements were found to approximate possible linear motion paths for every image voxel. The correction scheme was applied to free-breathing abdominal patient studies. In these scans, a reduction in artifacts from complex, nonrigid motion was observed.

On the significance of motion degradation in high-resolution 3D μMRI of trabecular bone

RATIONALE AND OBJECTIVES

Subtle subject movement during high-resolution three-dimensional micro-magnetic resonance imaging of trabecular bone (TB) causes blurring, thereby rendering the data unreliable for quantitative analysis. In this work, the effects of translational and rotational motion displacements were evaluated qualitatively and quantitatively.

MATERIALS AND METHODS

In experiment 1, motion was induced by applying various simulated and previously observed in vivo trajectories as phase shifts to k-space or rotation angles to k-space segments of a virtually motion-free data set. In experiment 2, images that were visually free of motion artifacts from two groups of 10 healthy individuals, differing in age, were selected to probe the effects of motion on TB parameters. In both experiments, images were rated for motion severity, and the scores were compared to a focus criterion, the normalized gradient squared.

RESULTS

Strong correlations were observed between the motion quality scores and the corresponding normalized gradient squared values (R(2) = 0.52-0.64, P < .01). The results from experiment 1 demonstrated consistently lower image quality and alterations in structural parameters of 9% to 45% with increased amplitude of displacements. In experiment 2, the significant differences in structural parameter group means of the motion-free images were lost upon motion degradation. Autofocusing, a postprocessing correction method, partially recovered the sharpness of the original motion-free images in 13 of 20 subjects.

CONCLUSIONS

Quantitative TB structural measures are highly sensitive to subtle motion-induced degradation, which adversely affects precision and statistical power. The results underscore the influence of subject movement in high-resolution three-dimensional micro-magnetic resonance imaging and its correction for TB structure analysis.

Hybrid prospective and retrospective head motion correction to mitigate cross-calibration errors

Utilization of external motion tracking devices is an emerging technology in head motion correction for MRI. However, cross-calibration between the reference frames of the external tracking device and the MRI scanner can be tedious and remains a challenge in practical applications. In this study, we present two hybrid methods, both of which combine prospective, optical-based motion correction with retrospective entropy-based autofocusing to remove residual motion artifacts. Our results revealed that in the presence of cross-calibration errors between the optical tracking device and the MR scanner, application of retrospective correction on prospectively corrected data significantly improves image quality. As a result of this hybrid prospective and retrospective motion correction approach, the requirement for a high-quality calibration scan can be significantly relaxed, even to the extent that it is possible to perform external prospective motion tracking without any prior cross-calibration step if a crude approximation of cross-calibration matrix exists. Moreover, the motion tracking system, which is used to reduce the dimensionality of the autofocusing problem, benefits the retrospective approach at the same time.

Intrinsic detection of motion in segmented sequences

While many motion correction techniques for MRI have been proposed, their use is often limited by increased patient preparation, decreased patient comfort, additional scan time, or the use of specialized sequences not available on many commercial scanners. For this reason, we propose a simple self-navigating technique designed to detect motion in segmented sequences. We demonstrate that comparing two segments containing adjacent sets of k-space lines results in an aliased error function. A global shift of the aliased error function indicates the presence of in-plane rigid-body translation, while other types of motion are evident in the dispersion or breadth of the error function. Since segmented sequences commonly acquire data in sets of adjacent k-space lines, this method provides these sequences with an inherent method of detecting object motion. Motion corrupted data can then be reacquired proactively or in some cases corrected or removed retrospectively.

Prospective motion correction of high-resolution magnetic resonance imaging data in children

Motion artifacts pose significant problems for the acquisition and analysis of high-resolution magnetic resonance imaging data. These artifacts can be particularly severe when studying pediatric populations, where greater patient movement reduces the ability to clearly view and reliably measure anatomy. In this study, we tested the effectiveness of a new prospective motion correction technique, called PROMO, as applied to making neuroanatomical measures in typically developing school-age children. This method attempts to address the problem of motion at its source by keeping the measurement coordinate system fixed with respect to the subject throughout image acquisition. The technique also performs automatic rescanning of images that were acquired during intervals of particularly severe motion. Unlike many previous techniques, this approach adjusts for both in-plane and through-plane movement, greatly reducing image artifacts without the need for additional equipment. Results show that the use of PROMO notably enhances subjective image quality, reduces errors in Freesurfer cortical surface reconstructions, and significantly improves the subcortical volumetric segmentation of brain structures. Further applications of PROMO for clinical and cognitive neuroscience are discussed.

Image metric-based correction (autofocusing) of motion artifacts in high-resolution trabecular bone imaging

PURPOSE

To evaluate the performance of the autofocusing (AF) motion correction technique in high-resolution trabecular bone imaging where image signal-to noise ratio (SNR) is limited.

MATERIALS AND METHODS

Raw data from 26 clinical three-dimensional (3D) wrist exams were motion corrected using AF for both in-plane rotation and translation. Changes in image metrics (a measurement of image sharpness) and structural parameters subsequently computed, were used to gauge the performance of the AF algorithm, and comparisons were made with translation-only navigator-corrected results.

RESULTS

On average, AF generated images with higher image sharpness compared to the navigator echo technique. The average normalized gradient squared (NGS) metric improved by 0.40%, 0.73%, and 0.84%, respectively, following translation-only navigator, translation-only AF and combined rotation/translation AF. For all structural parameters, the rotation/translation AF resulted in an approximately two-fold greater change compared to the navigator technique.

CONCLUSION

The data provide evidence that errors from subtle translational and rotational motion in the structural parameters in high-resolution trabecular bone images are alleviated by AF and that the resulting improvements are superior to translation-only 2D navigator correction.

Simulation of acquisition artefacts in MR scans: effects on automatic measures of brain atrophy

Automatic algorithms in conjunction with longitudinal MR brain images can be used to measure cerebral atrophy, which is particularly pronounced in several types of dementia. An atrophy simulation technique has been devised to facilitate validation of these algorithms. To make this model of atrophy more realistic we simulate acquisition artefacts which are common problems in dementia imaging: motion (both step and periodic motion) and pulsatile flow artefact. Artefacts were simulated by combining different portions of k-space from various modified image. The original images were 7 MR scans of healthy elderly controls, each of which had two levels of simulated atrophy. We investigate the effect of the simulated acquisition artefacts in atrophy measurements provided by an automatic technique, SIENA.

Quantitative MRI for the assessment of bone structure and function

Osteoporosis is the most common degenerative disease in the elderly. It is characterized by low bone mass and structural deterioration of bone tissue, leading to morbidity and increased fracture risk in the hip, spine and wrist-all sites of predominantly trabecular bone. Bone densitometry, currently the standard methodology for diagnosis and treatment monitoring, has significant limitations in that it cannot provide information on the structural manifestations of the disease. Recent advances in imaging, in particular MRI, can now provide detailed insight into the architectural consequences of disease progression and regression in response to treatment. The focus of this review is on the emerging methodology of quantitative MRI for the assessment of structure and function of trabecular bone. During the past 10 years, various approaches have been explored for obtaining image-based quantitative information on trabecular architecture. Indirect methods that do not require resolution on the scale of individual trabeculae and therefore can be practiced at any skeletal location, make use of the induced magnetic fields in the intertrabecular space. These fields, which have their origin in the greater diamagnetism of bone relative to surrounding marrow, can be measured in various ways, most typically in the form of R2', the recoverable component of the total transverse relaxation rate. Alternatively, the trabecular network can be quantified by high-resolution MRI (micro-MRI), which requires resolution adequate to at least partially resolve individual trabeculae. Micro-MRI-based structure analysis is therefore technically demanding in terms of image acquisition and algorithms needed to extract the structural information under conditions of limited signal-to-noise ratio and resolution. Other requirements that must be met include motion correction and image registration, both critical for achieving the reproducibility needed in repeat studies. Key clinical applications targeted involve fracture risk prediction and evaluation of the effect of therapeutic intervention.

Utility of fat-suppressed FLAIR and subtraction imaging in detecting meningeal abnormalities

We describe the use of a combination of fat-suppression SPIR (spectral inversion recovery) and subtraction FLAIR imaging to aid in detection of abnormal meningeal enhancement.

Improved optimization strategies for autofocusing motion compensation in MRI via the analysis of image metric maps

Autofocusing is a postprocessing technique for motion correction, which optimizes an image quality metric against various trial motions. In this work, image metric maps, which are measures of image quality plotted as a function of in-plane 2-D trial translations, are systematically studied to develop improved autofocusing motion correction algorithms. It is shown that determining object motion with autofocusing is equivalent to an image metric map optimization problem. These maps provide insights into the motion compensation process and help improve several aspects of the correction algorithm, including the selection of the image metric and motion search strategy. A highly efficient and robust 2-D global optimization method is devised, exploiting the properties of the metric map pattern. The improved algorithm is used to correct phantom and clinical MR images with in-plane 2-D translational motion and is shown to be more effective than existing methods.

Retrospective motion compensation using variable-density spiral trajectories

PURPOSE

To develop a method of retrospectively correcting for motion artifacts using a variable-density spiral (VDS) trajectory.

MATERIALS AND METHODS

Each VDS interleaf was designed to adequately sample the same center region of k-space. This central overlapping region can then be used to measure rigid body motion between the acquisition of each VDS interleaf. By applying appropriate phase shifts and rotations of the k-space data, rigid body motion artifacts can be removed, resulting in images with less motion corruption.

RESULTS

Both phantom and volunteer experiments are shown, demonstrating the technique's ability to further reduce artifacts in images acquired with an already motion-resistant acquisition trajectory. Registration accuracy is highly dependent on the trajectory design parameters. This space was explored to find an optimal design of VDS trajectories for motion compensation.

CONCLUSION

Using appropriately designed VDS trajectories, residual motion artifacts can be significantly reduced by retrospectively correcting for in-plane rigid body motion. An overlapping region of approximately 8% of the central region of k-space and approximately 70 interleaves were found to be near-optimal parameters for retrospective correction using VDS trajectories.

Automatic algorithm for correcting motion artifacts in time-resolved two-dimensional magnetic resoance angiography using convex projections

Time-resolved contrast enhanced magnetic resonance angiography (MRA) may suffer from involuntary patient motion. It is noted that while MR signal change associated with motion is large in magnitude and has smooth phase variation in k-phase, signal change associated with vascular enhancement is small in magnitude and has rapid phase variation in k-space. Based upon this observation, a novel projection onto convex sets (POCS) algorithm is developed as an automatic iterative method to remove motion artifacts. The presented POCS algorithm consists of high-pass phase filtering and convex projections in both k-space and image space. Without input of detailed motion knowledge, motion effects are filtered out, while vasculature information is preserved. The proposed method can be effective for a large class of nonrigid motions, including through-plane motion. The algorithm is stable and converges quickly, usually within five iterations. A double-blind evaluation on a set of clinical MRA cases shows that a completely unsupervised version of the algorithm produces significantly better rank scores (P=0.038) when compared to angiograms produced manually by an experienced radiologist.

Free-breathing whole-heart coronary MRA with 3D radial SSFP and self-navigated image reconstruction

Respiratory motion is a major source of artifacts in cardiac magnetic resonance imaging (MRI). Free-breathing techniques with pencil-beam navigators efficiently suppress respiratory motion and minimize the need for patient cooperation. However, the correlation between the measured navigator position and the actual position of the heart may be adversely affected by hysteretic effects, navigator position, and temporal delays between the navigators and the image acquisition. In addition, irregular breathing patterns during navigator-gated scanning may result in low scan efficiency and prolonged scan time. The purpose of this study was to develop and implement a self-navigated, free-breathing, whole-heart 3D coronary MRI technique that would overcome these shortcomings and improve the ease-of-use of coronary MRI. A signal synchronous with respiration was extracted directly from the echoes acquired for imaging, and the motion information was used for retrospective, rigid-body, through-plane motion correction. The images obtained from the self-navigated reconstruction were compared with the results from conventional, prospective, pencil-beam navigator tracking. Image quality was improved in phantom studies using self-navigation, while equivalent results were obtained with both techniques in preliminary in vivo studies.

Improvement of the image quality of T1-weighted anatomical brain scans

T1-weighted anatomical brain scans are routinely used in neuroimaging studies, for example, as anatomical reference for functional data and in brain morphometry studies. Subject motion can degrade the quality of these images. An additional problem is the occurrence of signal dropouts in the case of long echo times and low receiver bandwidths. These problems are addressed in two different studies. In the first study, it is shown that the high scalp signal, which results from the low T1 value of fat, may cause a typical ringing artefact in the presence of head motion. This problem may be enhanced if phased array coils are used for signal reception due to their increased sensitivity in the peripheral head regions. It is shown that this artefact can be avoided by combining certain fat suppression techniques that reduce the scalp signal. In the second study, it is shown that signal dropout affects mainly the orbitofrontal cortex and the temporal lobes, and that a bandwidth of 100 Hz/pixel should be chosen for the investigation of these areas to avoid signal losses while maintaining an acceptable signal-to-noise ratio. Experimental results are based on the MDEFT sequence but can be applied to other T1-weighted sequences like FLASH and MP-RAGE. Furthermore, the presented methods for improving the image quality can be combined with other artefact reduction techniques.

A review of technical advances in interventional magnetic resonance imaging

Initial research in the development of interventional magnetic resonance (MR) imaging in the late 1980s and early to mid-1990s focused on pulse sequences, devices, and clinical applications. This focus was largely a result of the limited number of areas in which the academic research community leading the development could provide innovation on the MR systems of the time. However, during the past decade, computational power, higher bandwidth graphical displays, faster computer networks, improved pulse sequence architectures, and improved technical specifications have accelerated the pace of development on modern MR systems. Today, it is the combination of multiple system factors that are enabling the future of interventional MR. These developments, their impact on the field, and newly emerging applications are described.

Correcting bulk in-plane motion artifacts in MRI using the point spread function

A technique is proposed for correcting both translational and rotational motion artifacts in magnetic resonance imaging without the need to collect additional navigator data or to perform intensive postprocessing. The method is based on measuring the point spread function (PSF) by attaching one or two point-sized markers to the main imaging object. Following the isolation of a PSF marker from the acquired image, translational motion could be corrected directly from the modulation transfer function, without the need to determine the object's positions during the scan, although the shifts could be extracted if desired. Rotation is detected by analyzing the relative displacements of two such markers. The technique was evaluated with simulations, phantom and in vivo experiments.

Motion-correction techniques for standing equine MRI

Magnetic resonance imaging (MRI) of the distal extremities of the standing, sedated horse would be desirable if diagnostic quality images could be obtained. With the availability of extremity and special purpose magnet designs on the market, a system to safely accommodate the standing horse may gain increasing popularity. This paper considers the issue of motion that will need to be addressed to achieve successful, diagnostic quality images. The motion of the carpus and tarsus of five standing, sedated horses was quantified. The obtained motion records were then used to induce motion in cadaveric joint specimens during several MRI scans. The measured dorsal-palmar/plantar, medial-lateral, and proximal-distal random wobbling motions in the standing sedated horse were several centimeters in magnitude and generated severe motion-artifacts during axial MRI of the cadaveric specimens. Two retrospective motion-correction techniques (autocorrection and navigator-based adaptive correction) were used to correct the corrupted images. The motion artifacts were nearly eliminated with the use of both techniques in series. Although significant hurdles remain, these results suggest promise for allowing diagnostic quality MRI of the carpus and tarsus in the standing horse.

Single spin-echo proton transverse relaxometry of iron-loaded liver

A single-spin-echo methodology is described for the measurement and imaging of proton transverse relaxation rates (R2) in iron-loaded and normal human liver tissue in vivo. The methodology brings together previously reported techniques dealing with (i) the changes in gain between each spin-echo acquisition, (ii) signal level offset due to background noise, (iii) estimation of signal intensities in decay curves at time zero to enable reliable extraction of relaxation times from tissues with very short T2 values, (iv) bi-exponential modelling of decay curves with a small number of data points, and (v) reduction of respiratory motion artefacts. The accuracy of the technique is tested on aqueous manganese chloride solutions yielding a relaxivity of 74.1+/-0.3 s-1 (mM)-1, consistent with previous reports. The precision of the in vivo measurement of mean liver R2 values is tested through duplicate measurements on 10 human subjects with mean liver R2 values ranging from 26 to 220 s-1. The random uncertainty on the measurement of mean liver R2 was found to be 7.7%.

Artifact reduction using parallel imaging methods

Multiple receiver coils produce images with different but complementary views of a patient. This can be used to shorten scans times but there often remain image artifacts caused by patient motion or physiological processes such as flowing blood. This paper reviews how the extra information from the multiple coils can be used to reduce image artifacts. In one method, affected portions of data can be identified and discarded but enough information is still available to reconstruct an improved image. In other methods, the motion itself is determined and the corrupted data is then corrected, leading to an image with reduced artifacts. Results are presented from images corrupted by motion or by flowing blood.

A method of generalized projections (MGP) ghost correction algorithm for interleaved EPI

Investigations into the method of generalized projections (MGP) as a ghost correction method for interleaved EPI are described. The technique is image-based and does not require additional reference scans. The algorithm was found to be more effective if a priori knowledge was incorporated to reduce the degrees of freedom, by modeling the ghosting as arising from a small number of phase offsets. In simulations with phase variation between consecutive shots for n-interleaved echo planar imaging (EPI), ghost reduction was achieved for n = 2 only. With no phase variation between shots, ghost reduction was obtained with n up to 16. Incorporating a relaxation parameter was found to improve convergence. Dependence of convergence on the region of support was also investigated. A fully automatic version of the method was developed, using results from the simulations. When tested on in vivo 2-, 16-, and 32-interleaved spin-echo EPI data, the method achieved deghosting and image restoration close to that obtained by both reference scan and odd/even filter correction, although some residual artifacts remained.

Reduction of respiratory motion artifacts in transverse relaxation rate (R2) images of the liver

An empirical motion artifact suppression technique has been developed to reduce the respiratory motion artifacts in axial single spin-echo magnetic resonance (MR) images of the liver post-acquisition. The correction scheme is based on the observation that the dominant motion artifacts within abdominal MR images are ghosts that follow the profile and signal intensity of high signal intensity boundaries, such as those for the subcutaneous fat along the anterior abdominal wall. The technique is applied to the reduction of respiratory motion artifacts in a spin echo image series of the liver of an iron-loaded patient and of a manganese chloride phantom subject to respiratory motion. Subsequent improvements to transverse relaxation rate (R2) image analysis are then demonstrated on the motion-corrected spin echo images, illustrating the utility of the technique for application in the R2 image-based measurement and mapping of liver iron concentration.

RINGLET motion correction for 3D MRI acquired with the elliptical centric view order

A new rigid-body motion correction algorithm is described that is compatible with 3D image sets acquired with the elliptical centric (EC) view order. With this view order, an annular ring of k-space data is acquired in the ky-kz plane during any short time interval. Images for tracking motion can be reconstructed in the yz-plane from any ring of the acquisition data. In these tracking images, a point source (such as an external marker) shows a characteristic bull's-eye pattern that permits motion monitoring and correction. The true position of the point object is located at the center of the bull's-eye pattern. Cross correlation can be performed to automatically track the positions of markers reconstructed from adjacent rings of k-space. To increase the marker signal, the markers are encased in inductively coupled RF coils. Rigid-body motion in the yz-plane is calculated directly with the Euclidean group for rotation and translation, and corrected by rotating and applying phase shifts to any corrupted rings of data. In the current work we present a theoretical analysis of this method, as well as results of volunteer and controlled phantom experiments that demonstrate its initial feasibility. Although the EC view order has mainly been used for MR angiography (MRA), it can also be used for most 3D acquisitions.

Coronary MR angiography: respiratory motion correction with BACSPIN

PURPOSE

To improve the signal-to-noise ratio (SNR) of breath-held coronary magnetic resonance angiography (CMRA) without increasing the number or duration of breath holds.

MATERIALS AND METHODS

In this BACSPIN (Breathing AutoCorrection with SPiral INterleaves) technique, a single breath-held electrocardiogram (ECG)-gated multi-slice interleaved-spiral data set is acquired, followed by repeated imaging of the same slices during free breathing. Each spiral interleaf from the breath-held data set is used as a standard for comparison with corresponding acquisitions at the same interleaf angle during free breathing. The most closely matched acquisitions are incorporated into a multi-slice, multi-average data set with increasing SNR over time. In-plane translations of the coronary artery can be measured and compensated for each accepted acquisition before combination with the other acquisitions.

RESULTS

CMRA was performed on six volunteers, with improved SNR and minimal motional blurring. In some cases, breath holding could be dispensed with completely and the average respiratory position used as a reference.

CONCLUSION

BACSPIN provides a promising method for CMRA with improved SNR and limited breath-holding requirements.

Motion correction using the k-space phase difference of orthogonal acquisitions

Rigid body translations of an object in MRI create image artifacts along the phase-encode (PE) direction in standard 2DFT imaging. If two images are acquired with swapped PE direction, it is possible to determine and correct for arbitrary in-plane translational interview motions in both images directly from phase differences in the k-space acquisitions by solving a large system of linear equations. For example, if one assumes two N x N 2D acquisitions with in-plane translational interview motion, 4N unknown motions may corrupt the two images, but the phase difference at each point in k-space yields a system of N(2) equations in these 4N unknowns. If the acquisitions have orthogonal PE directions, this highly overdetermined system of equations can be solved to provide the motion records, which in turn can be used to correct the motion artifacts in each image. The theory of this orthogonal k-space phase difference (ORKPHAD) technique is described, and results are presented for synthetic and in vivo motion-corrupted data sets. In all cases, the data showed clear improvement of translation-induced artifacts. These methods do not require special pulse sequences and are theoretically generalizable to partial Fourier imaging and 3D acquisitions.

Motion artifact in magnetic resonance imaging: implications for automated analysis

Automated measures of cerebral magnetic resonance images (MRI) often provide greater speed and reliability compared to manual techniques but can be particularly sensitive to motion artifact. This study employed an automatic MRI analysis program that quantified regional gray matter volume and created images for verification and quality control. Motion artifact was assessed on each image and assigned a rating of none, mild, moderate, or severe. Greater motion artifact was associated with smaller gray matter volumes. Severity of motion artifact is an important, but often overlooked, consideration in the interpretation of automated MRI measures.

Image-based EPI ghost correction using an algorithm based on projection onto convex sets (POCS)

This work describes the use of a method, based on the projection onto convex sets (POCS) algorithm, for reduction of the N/2 ghost in echo-planar imaging (EPI). In this method, ghosts outside the parent image are set to zero and a model k-space is obtained from the Fourier transform (FT) of the resulting image. The zeroth- and first-order phase corrections for each line of the original k-space are estimated by comparison with the corresponding line in the model k-space. To overcome problems of phase wrapping, the first-order phase corrections for the lines of the original k-space are estimated by registration with the corresponding lines in the model k-space. It is shown that applying these corrections will result in a reduction of the ghost, and that iterating the process will result in a convergence towards an image in which the ghost is minimized. The method is tested on spin-echo EPI data. The results show that the method is robust and remarkably effective, reducing the N/2 ghost to a level nearly comparable to that achieved with reference scans.

Autocorrection of three-dimensional time-of-flight MR angiography of the Circle of Willis

OBJECTIVE

The purpose of this study was to investigate the efficacy of a retrospective adaptive motion correction technique known as autocorrection for reducing motion-induced artifacts in high-resolution three-dimensional time-of-flight MR angiography of the circle of Willis.

MATERIALS AND METHODS

Ten consecutive volunteers were imaged with an unenhanced gradient-recalled echo three-dimensional time-of-flight MR angiography sequence of the circle of Willis. Each volunteer was asked to rotate approximately 2 degrees after completion of one third and one half of the acquisition in the axial, sagittal, and oblique planes (45 degrees to the axial and sagittal planes). A single static data set was also acquired for each volunteer. Unprocessed and autocorrected maximum-intensity-projection images were reviewed as blinded image pairs by six radiologists and were compared on a five-point image quality scale.

RESULTS

Mean improvement in image quality after autocorrection was 1.4 (p < 0.0001), 1.1 (p < 0.0001), and 0.2 (p = 0.003) observer points (maximum value, 2.0), respectively, for examinations corrupted by motion in the axial, oblique, and sagittal planes. All three axes had statistically significant improvement in image quality compared with the uncorrected images. Changes in image quality after the application of the autocorrection algorithm to static angiogram data were not statistically significant (mean change in score = -0.13 points; p = 0.29).

CONCLUSION

Autocorrection can reduce artifacts in motion-corrupted MR angiography of the circle of Willis without distorting motion-free examinations.